Paper
27 June 1996 Target recognition, identification, and tracking using real and synthetic IR imagery
H. Tim A. Pentecost, Andrew M. Rogoyski, Douglas R. McCann, Andrew J. Maurice
Author Affiliations +
Abstract
In the development of automatic target detection (ATD) and automatic target recognition/identification (ATR/I) systems, the issue of image data is commonly given inadequate consideration. All too often a poorly managed collection of real data, or unrealistic synthetic data is used during development, resulting in a loss of performance when used in the field with imagery having different characteristics. Some of the most promising approaches to ATD and ATR/I, such as neural networks, are particularly susceptible to this problem due to their direct dependence on the training data. This paper highlights the issues involved, with reference to a generic detection and classification approach and to the use of real and synthetic infra-red imagery at the Defence Research Agency at Fort Halstead in the United Kingdom.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
H. Tim A. Pentecost, Andrew M. Rogoyski, Douglas R. McCann, and Andrew J. Maurice "Target recognition, identification, and tracking using real and synthetic IR imagery", Proc. SPIE 2744, Infrared Technology and Applications XXII, (27 June 1996); https://doi.org/10.1117/12.243492
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Neural networks

Image classification

Target recognition

Feature extraction

Image processing

Target detection

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